AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | Hybrid | San Jose, CA

Enigma; San Jose (CA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Enigma is seeking an AI Research Scientist to drive machine learning research from concept to production in a hybrid environment in San Jose, CA. You will design experiments, evaluate baselines, and collaborate with product teams to shape real-world AI features.

Ideal candidates have 3–5 years in AI/ML research, a strong publication record or potential, and hands-on experience with PyTorch, PEFT/LoRA, and RLHF techniques. PhD preferred but Master’s with exceptional work will be considered.

Qualifications

• PhD in CS/AI/ML or related field is strongly preferred.
• Master’s degree with exceptional research or industry experience will be considered.
• 3–5 years in AI/ML research, ideally in applied or product-focused environments.

Responsibilities

• Design, execute, and analyze machine learning experiments with strong baselines and evaluation metrics.
• Stay up to date with AI research; identify, adapt, and validate novel techniques for company-specific use cases.
• Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial testing to ensure statistical soundness.
• Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes.
• Collaborate with domain experts, product managers, and engineering teams to refine problem statements and operational constraints.
• Develop reusable research assets such as datasets, modular code components, evaluation suites, and documentation.
• Work alongside ML Engineers to optimize training and inference pipelines for production systems.
• Contribute to academic publications and represent the company in research communities.

Skills

Machine learning

Deep learning

NLP

PEFT/LoRA

Adapters

RLHF/RLAIF

Python

C++

Java

PyTorch

Hugging Face

NumPy

Mathematics

LLMs

Education

PhD in Computer Science, AI, ML, or related field

Master’s degree with exceptional research or industry experience

Tools

PyTorch

Hugging Face

NumPy

Job description

Responsibilities:

• Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics.
• Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases.
• Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness.
• Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes.
• Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints.
• Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation.
• Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems.
• Contribute to academic publications and represent the company in research communities, as needed.

Educational Qualifications:

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred.
• Candidates with a master’s degree and exceptional research or industry experience will also be considered.

Industry Experience:

• 3–5 years of experience in AI/ML research roles, ideally in applied or product-focused environments.
• Demonstrated success in delivering research-driven solutions that have been deployed in production.
• Experience collaborating in cross-functional teams across research, engineering, and product.
• Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus.

Technical Skills:

• Strong foundational knowledge in machine learning and deep learning algorithms.
• Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO).
• Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases.
• Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations.
• Advanced programming skills in Python (preferred), C++, or Java.
• Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc.
• Strong mathematical foundations in probability, linear algebra, and calculus.
• Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc.
• Ability to translate research insights into roadmaps, technical specifications, and product improvements.

AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | Hybrid | San Jose, CA

AI Research Scientist | Machine Learning | Deep Learning |Natural Language Processing | LLM | Hybrid | San Jose, CA